"CMTMU Dataset \u2014 Comprehensive multi-type and multi-unit appliance dataset"

"To advance real-world applications of non-intrusive load monitoring (NILM), we propose the CMTMU dataset\u2014an innovative dataset that simulates realistic residential power consumption scenarios involving both multiple appliance types and multiple units of the same type. Existing NILM datasets largely overlook such complexity, limiting model generalizability. The CMTMU dataset is constructed by applying an offset-overlay technique to REFIT data, enabling the simulation of concurrent multi-unit appliance usage. Furthermore, a margin-based event detection mechanism and threshold-based labeling strategy are used to annotate appliance states with high fidelity. CMTMU includes diverse appliance categories such as fridges, kettles, washing machines, and dishwashers, capturing realistic load variations and operational overlaps. Experimental results using state-of-the-art NILM models demonstrate that the CMTMU dataset significantly enhances the training and evaluation of models under complex appliance operation conditions, thereby promoting more accurate load disaggregation and appliance quantity identification in smart energy systems."